You can not select more than 25 topics Topics must start with a chinese character,a letter or number, can include dashes ('-') and can be up to 35 characters long.

144.csv 3.4 kB

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566
  1. 3.000000000000000000e+01,8.000000000000000000e+00
  2. 9.600000000000000000e+01,-3.200000000000000000e+01
  3. 2.100000000000000000e+02,-1.400000000000000000e+02
  4. 2.800000000000000000e+02,-8.000000000000000000e+01
  5. 2.100000000000000000e+02,4.700000000000000000e+01
  6. 8.200000000000000000e+01,2.200000000000000000e+01
  7. -4.600000000000000000e+01,7.400000000000000000e+01
  8. -4.800000000000000000e+01,1.400000000000000000e+02
  9. -1.800000000000000000e+01,2.060000000000000000e+02
  10. -6.600000000000000000e+01,3.000000000000000000e+02
  11. -7.000000000000000000e+01,2.820000000000000000e+02
  12. -5.000000000000000000e+01,1.540000000000000000e+02
  13. -6.600000000000000000e+01,2.600000000000000000e+01
  14. -1.360000000000000000e+02,-1.200000000000000000e+01
  15. -1.320000000000000000e+02,-1.600000000000000000e+01
  16. -1.500000000000000000e+02,-2.000000000000000000e+01
  17. -1.380000000000000000e+02,-3.000000000000000000e+01
  18. -1.860000000000000000e+02,-2.600000000000000000e+01
  19. -1.860000000000000000e+02,-2.400000000000000000e+01
  20. -1.720000000000000000e+02,-2.800000000000000000e+01
  21. -1.860000000000000000e+02,-4.000000000000000000e+01
  22. -2.320000000000000000e+02,-3.600000000000000000e+01
  23. -2.640000000000000000e+02,-2.800000000000000000e+01
  24. -2.520000000000000000e+02,-4.200000000000000000e+01
  25. -2.860000000000000000e+02,-5.400000000000000000e+01
  26. -3.140000000000000000e+02,-5.600000000000000000e+01
  27. -3.220000000000000000e+02,-7.200000000000000000e+01
  28. -3.220000000000000000e+02,-7.600000000000000000e+01
  29. -3.300000000000000000e+02,-9.800000000000000000e+01
  30. -3.320000000000000000e+02,-8.000000000000000000e+01
  31. -2.680000000000000000e+02,-9.200000000000000000e+01
  32. -2.340000000000000000e+02,-1.040000000000000000e+02
  33. -2.100000000000000000e+02,-1.080000000000000000e+02
  34. -1.880000000000000000e+02,-1.160000000000000000e+02
  35. -1.240000000000000000e+02,-9.000000000000000000e+01
  36. -5.800000000000000000e+01,-9.200000000000000000e+01
  37. -2.400000000000000000e+01,-8.000000000000000000e+01
  38. 1.200000000000000000e+01,-6.000000000000000000e+01
  39. 5.200000000000000000e+01,-5.000000000000000000e+01
  40. 7.400000000000000000e+01,-3.800000000000000000e+01
  41. 1.000000000000000000e+02,-2.800000000000000000e+01
  42. 9.800000000000000000e+01,-1.400000000000000000e+01
  43. 9.600000000000000000e+01,-8.000000000000000000e+00
  44. 1.060000000000000000e+02,-8.000000000000000000e+00
  45. 1.080000000000000000e+02,6.000000000000000000e+00
  46. 9.600000000000000000e+01,2.000000000000000000e+01
  47. 1.040000000000000000e+02,1.200000000000000000e+01
  48. 1.000000000000000000e+02,2.000000000000000000e+01
  49. 9.400000000000000000e+01,3.000000000000000000e+01
  50. 8.800000000000000000e+01,2.000000000000000000e+01
  51. 1.020000000000000000e+02,2.800000000000000000e+01
  52. 6.600000000000000000e+01,2.600000000000000000e+01
  53. 1.200000000000000000e+02,1.600000000000000000e+01
  54. 1.100000000000000000e+02,2.200000000000000000e+01
  55. 1.080000000000000000e+02,2.400000000000000000e+01
  56. 1.080000000000000000e+02,2.200000000000000000e+01
  57. 1.120000000000000000e+02,4.400000000000000000e+01
  58. 1.320000000000000000e+02,4.800000000000000000e+01
  59. 1.540000000000000000e+02,5.200000000000000000e+01
  60. 1.360000000000000000e+02,4.000000000000000000e+01
  61. 2.000000000000000000e+02,1.800000000000000000e+01
  62. 1.900000000000000000e+02,-2.000000000000000000e+01
  63. 1.080000000000000000e+02,-4.600000000000000000e+01
  64. -2.000000000000000000e+01,-1.200000000000000000e+02
  65. -1.480000000000000000e+02,-2.480000000000000000e+02
  66. -2.760000000000000000e+02,-3.760000000000000000e+02

全栈的自动化机器学习系统,主要针对多变量时间序列数据的异常检测。TODS提供了详尽的用于构建基于机器学习的异常检测系统的模块,它们包括:数据处理(data processing),时间序列处理( time series processing),特征分析(feature analysis),检测算法(detection algorithms),和强化模块( reinforcement module)。这些模块所提供的功能包括常见的数据预处理、时间序列数据的平滑或变换,从时域或频域中抽取特征、多种多样的检测算